Reproducible imaging-based brain growth charts for psychiatry

用于精神病学的可重复的基于成像的大脑生长图

• 批准号: 10430126
• 负责人: Michael Peter Milham
• 金额: $ 66.57万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-22 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10430126
• 关键词: Address; Adolescence; Age; Base of the Brain; Bayesian Method; Brain; Brain Diseases; Categories; Childhood; Clinical; Clinical Data; Code; Communities; Data; Data Aggregation; Data Analytics; Data Collection; Data Pooling; Data Set; Detection; Development; Diagnosis; Dimensions; Disease; Docking; Early Intervention; Failure; Fright; Functional Imaging; Grain; Growth; Heterogeneity; Human; Image; Informatics; International; Life; Link; Machine Learning; Maps; Measurement; Measures; Mental disorders; Modeling; Multimodal Imaging; National Institute of Mental Health; Neurosciences; Outcome; Participant; Phenotype; Process; Properdin; Protocols documentation; Psychiatry; Psychopathology; Public Health; Recording of previous events; Reproducibility; Research; Resources; Rest; Sampling; Scanning; Sex Differences; Site; Societies; Sum; Symptoms; Techniques; Training; Validation; Variant; Youth; aging brain; anxious; base; brain abnormalities; clinical phenotype; computing resources; cost; data archive; data harmonization; data integration; data resource; design; disability; externalizing behavior; image processing; imaging study; indexing; insight; instrument; machine learning method; multidimensional data; multimodal neuroimaging; neuroimaging; novel; portability; quality assurance; response; segregation; serial imaging; sex; somatosensory; synergism; theories; young adult

ABSTRACT Major psychiatric illnesses are increasingly understood as disorders of brain development, which has led to large-scale studies of youth that combine multi-modal neuroimaging with clinical phenotyping. Together, such data have emphasized the promise of objective ‘growth charts’ of brain development. However, synergies across major efforts remains unrealized due to use of different clinical instruments, different scanning protocols, challenges in informatics, and difficulties in data integration. In this proposal, we will overcome these obstacles by leveraging advances in multivariate harmonization and analysis techniques to build highly reproducible growth charts of human brain development. To do this, we will aggregate and harmonize eight existing large-scale developmental imaging studies, comprising over 10,000 participants between the age of 5- 24 (Aim 1). We will use this harmonized data to build generalizable indices of normal network brain development (Aim 2). Finally, developmental abnormalities within specific brain networks will be linked to dimensions of psychopathology (Aim 3). Critically, all code, data, and derived indices will be shared publicly, creating a massive new resource to accelerate research in the developmental neuroscience community (Aim 4). In sum, this proposal will have provide a new data resource, yield reproducible growth charts of brain development, and delineate novel mechanisms regarding the developmental basis of psychopathology in youth.

摘要 主要的精神疾病越来越被理解为大脑发育障碍，这导致了 联合收割机多模态神经成像与临床表型相结合的大规模青年研究。一起的 数据强调了大脑发育的客观“生长图”的前景。然而，协同作用 由于使用了不同的临床仪器、不同的扫描方法， 协议，信息学的挑战和数据集成的困难。在这份提案中，我们将克服 利用多元协调和分析技术的进步， 人类大脑发育的可复制的生长图表。为了做到这一点，我们将汇总和协调八个 现有的大规模发育成像研究，包括超过10，000名5岁至 24（目标1）。我们将使用这些协调的数据来建立正常网络脑的可推广指标 发展（目标2）。最后，特定大脑网络中的发育异常将与 精神病理学的维度（目标3）。重要的是，所有代码、数据和派生索引都将公开共享， 创建一个巨大的新资源，以加速发展神经科学界的研究（Aim 4）。总之，该方案将提供一种新的数据源，产生可重复的脑生长图 发展，并描绘新的机制，关于发展的基础上，精神病理学， 青年